class_docstr: Feature loader that load external features store in certain format. 
  Currently support pickle, npy and npz format.
code: def process_segment(self, feature_segment):
      if self.augmentor:
          # augmentor for external features. Here possible augmentor for external embedding feature is Diaconis Augmentation and might be implemented later
          self.augmentor.perturb(feature_segment)
          return torch.tensor(feature_segment, dtype=torch.float)
  
      return torch.tensor(feature_segment, dtype=torch.float)
  
file_path: NeMo/nemo/collections/asr/parts/preprocessing/feature_loader.py
imports: from typing import Optional
  import numpy
  import torch
label_desc: Use image node_id 5 for calling the ExternalFeatureLoader obj's underlying member method code with example usage: obj.process_segment(feature_segment) and returns: torch, torch